The present invention relates in general to communication systems, and is particularly directed to a new and improved signal processing mechanism for rapidly and optimally setting weighting coefficient values of respective elements of a multi-element antenna, such as a phased array antenna employed to controllably form a beam whose gain and/or nulls are defined so as to maximize the signal to noise ratio. Such improved functionality makes the invention particularly useful in association with the phased array antenna of a base station of a time division multiple access (TDMA) cellular communication system, where it is necessary to cancel interference from co-channel users located in cells adjacent to the cell containing a desired user and the base station.
As described in the above-referenced ""287 Halford et al application, in a TDMA cellular communication system, a simplified illustration of which is diagrammatically shown in FIG. 1, communications between a base station BS and a desired user 11-1 in a centroid cell 11 are subject to potential interference by co-channel transmissions from users in cells dispersed relative to the cell of interest (cell 11), particularly immediately adjacent cells shown at 21-71. This potential for co-channel interference is due to the fact that the same frequency is assigned to multiple system users, who transmit during respectively different time slots.
In the non-limiting simplified example of FIG. 1, where each cell has a time division reuse allocation of three (a given channel is subdivided into three user time slots), preventing interference with communications between user 11-1 and its base station BS from each co-channel user in the surrounding cells 21-71 would appear to be an ominous taskxe2x80x94ostensibly requiring the placement of eighteen nulls in the directivity pattern of the antenna employed by the centroid cell""s base station BS.
In accordance with the invention disclosed in the application, this problem is successfully addressed by ""287 determining the times of occurrence of synchronization patterns of monitored co-channel transmissions from users in the adjacent cells, and using this timing information to periodically update a set of amplitude and phase weights (weighting coefficients) for controlling the directivity pattern of a phased array antenna. Namely, the weighting coefficients are updated as participants in the pool of interferers change (in a time division multiplexed manner), so as to maintain the desired user effectively free from co-channel interference sourced from any of the adjacent cells.
In addition to being applied to the weighting elements, the updated weighting coefficients are stored in memory until the next cyclically repeating occurrence of the time slot of the last (in time) entry in the current pool of co-channel participants. In response to this next occurrence, the set of weight control values for the current pool is updated and used to adjust the phased array""s directivity pattern, so that the nulls in the directivity pattern effectively follow co-channel users of adjacent cells. The newly updated weight set is then stored until the next (periodically repeated) update interval for the current co-channel user pool, and so on.
Since the maximum number of nulls than can be placed in the directivity pattern of a phased array antenna is only one less than the number of elements of the array, the fact that the number of TDMA co-channel interferers who may be transmitting at any given instant is a small fraction of the total number of potential co-channel interferers (e.g., six versus eighteen in the above example) allows the hardware complexity and cost of the base station""s phased array antenna to be considerably reduced. However, because the locations of co-channel interferers and therefore the placement of nulls is dynamic and spatially variable, the antenna directivity pattern must be controlled very accurately; in particular, excessive sidelobes that are created by grating effects customarily inherent in a phased array having a spatially periodic geometry must be avoided.
In accordance with the invention described in the above-referenced ""476 Hildebrand er al application, and diagrammatically illustrated in FIGS. 2 and 3, this unwanted sidelobe/grating effect is minimized by using a spatially aperiodic phased array geometry, in which a plurality of N antenna elements (such as dipole elements) 31, 32, 33, . . . , 3N are unequally distributed or spaced apart from one another in a two-dimensional, generally planar array 30, shown as lying along a circle 40 having a center 41. This unequal distribution is effective to decorrelate angular and linear separations among elements of the array.
Each dipole 3i of the circular array is oriented orthogonal to the plane of the array, so as to produce a directivity pattern that is generally parallel to the plane of the array. Via control of amplitude and phase weighting elements coupled in the feed for each dipole element, the composite directivity pattern of the array is controllably definable to place a main lobe on a desired user, and one or more nulls along (Nxe2x88x921) radial lines xe2x80x98rxe2x80x99 emanating from the center 41 of the array toward adjacent cells containing potential interfering co-channel users. Namely, for any angle of incidence of a received signal, the vector distance from any point along that radial direction to any two elements of the array is unequal and uniformly distributed in phase (modulo 2xcfx80).
What results is a spatially decorrelated antenna element separation scheme, in which no two pairs of successively adjacent antenna elements have the same angular or chord separation. Without spacial correlation among any of the elements of the array, sidelobes of individual elements, rather than constructively reinforcing one another into unwanted composite sidelobes of substantial magnitude, are diminished, thereby allowing nulls of substantial depth to be placed upon co-channel interferers.
As further described in the ""287 Halford et al application, non-limiting examples of weighting coefficient algorithms that may be employed for determining the values of the weighting coefficients and thereby the directivity pattern of the base station""s phased array antenna include the xe2x80x9cMaximum SNR Method,xe2x80x9d described in the text xe2x80x9cIntroduction to Adaptive Arrays,xe2x80x9d by R. Monzingo et al, published 1980, by Wiley and Sons, N.Y., and the PSF algorithm described in U.S. Pat. No. 4,255,791 (the ""791 patent) to P. Martin, entitled: xe2x80x9cSignal Processing System,xe2x80x9d issued Mar. 10, 1981, assigned to the assignee of the present application and the disclosure of which is herein incorporated.
The present invention is directed to an alternative approach to the PSF algorithm described in the abovereferenced ""791 patent, that is particularly useful in a dynamic environment, such as a TDM cellular communication system environment, in which the number of and spatial location of participants may undergo changes, mandating the need for a weighting coefficient control mechanism that is able to make rapid real time adjustments with effectively little or no knowledge of the environment being addressed.
Pursuant to the invention, this objective is successfully achieved by an iterative or xe2x80x98bootstrappedxe2x80x99, piecewise-asymptotic directivity pattern control mechanism, that is operative to continuously monitor signals as received by a plurality of antenna elements and to process these signals in accordance with an iterative weighting coefficient processing mechanism, so as to produce a set of (amplitude and phase) weighting coefficients through which the directivity pattern is controlled so as to maximize the signal to noise ratio. The received signals for the monitored user channel of interest, as modified by the adaptively updated weighting coefficients, are then output to a downstream demodulator.
In order for the adaptive weighting coefficient control mechanism of the present invention to xe2x80x98bootstrapxe2x80x99 itself, it starts off with a relatively coarse, but reasonably well defined set of weighting coefficients, that have a positive signal-to-noise ratio, such as a bit error rate on the order of one in ten, as a non-limiting example. The actual signals received by the antenna elements are modified by this initial set of weights to produce a first set of estimates of the information signal contents of the received signals. Using this initial set of signal estimates and the actual signals received by the antenna elements (and buffered as necessary for iterative signal processing, as will be described), the initial set of weighting coefficients are refined by means of a prescribed signal processing operator.
The signal processing operator includes a data decision unit, to which the modified received signal estimates are supplied, and a signal transform operator, to which both the unmodified or xe2x80x98rawxe2x80x99 data representative of the received signals from the antenna elements and the output of the data decision unit are applied. If a priori knowledge of the signal is available, the data decision unit may comprise a data demodulator or other similar component, that uses such knowledge to derive an initial data estimate output signal. Alternatively, the data decision unit may comprise a relatively simple signal processing component, such as a hard-limiter or bit-slice unit, that does not require a priori knowledge of the signal, as long as the received signal has some degree of coherence.
Using the signal processing scheme described in the above-identified ""791 patent, the signal transform operator produces an output containing two componentsxe2x80x94one containing the desired information signal component S(t) and a noise component n(t) of the form Ad(t)cos(xcfx89t+xcfx86)+n(t), where d(t) is data and A is amplitude, and the other of which is a transformed noise signal component xcex7(t) that is uncorrelated with any other signal, including the noise component n(t). Since the transformed noise signal component xcex7(t) is uncorrelated with any other signal, then the correlated energy E is such that E((n(t)*S(t))=0,E((xcex7(t)*n(t))=0, and E((xcex7(t)*S(t))=0, leaving only E((S(t)*S(t)) proportional to S2(t).
The actually received signal input (S+N) and the output (S+xcex7) of the signal transform operator are applied to a correlationxe2x88x92multiplier operator to produce a noise signal set/matrix (xcex7xe2x88x92N). The individual signal components of the signal input (S+N) are multiplied by signal components of the output (S+xcex7), while the components of the noise signal set/matrix (xcex7xe2x88x92N) are multiplied to produce a desired signal covariance matrix Rs and a noise covariance matrix Rn. In order to derive the actual values of the updated weighting coefficients, these desired signal and noise covariance matrices Rs and Rn are applied to a coefficient multiplier, which generates the matrix product of the inverse of the noise covariance matrix Rnxe2x88x921, the useful signal matrix Rs and the previous values of the weighting coefficients W. This matrix product is a set of refined or updated set of weighting coefficients Wu, that replace the previous set of weights, such as an initial set of weights used at the start of the iterative process. The temporarily buffered signals are then modified by the updated weights Wu via a matrix multiplier, to produce an xe2x80x98improvedxe2x80x99 signal estimate.
For each subsequent iteration of the weighting coefficient update sequence, the values of the signal estimates are applied to the data decision unit in place of the previous estimates. Since the updated weighting coefficients produce better estimates of the received signals, the improved signal estimates will result in more accurate weighting coefficients at the next iteration. Analysis has shown that the degree of improvement of each iteration follows a non-linear track, that is asymptotic to some final xe2x80x98idealxe2x80x99 value, and that the improvement differential between sequential iterations along this asymptotic variation typically becomes very small after only a small number of iterations, e.g., only two in the case of a TDM cellular system. This rapid iterative asymptotic refinement is significant in real time or quasi real time signal processing applications, where throughput delay must. be minimized. The number of iterations is preferably determined by simulating the signal processing application of interest.